IEEE - Aerospace and Electronic Systems - August 2023 - 32
Incremental Deinterleaving of Radar Emitters
Figure 4.
Example of a simulated PDW scene (100 ms) with six radars in the X-band (ground truth coloring). FA pulses are colored in gray.
we propose a new balancing technique for ARI. It guarantees,
that each radar emitter has equal influence on the ARI regardless
of the number of pulses. The proposed balanced ARI is
calculated as follows.
1) Calculate the ARI on only a random subset of the
pulses. The subset is chosen such that all emitters
have equal number of pulses. This process is
repeated several times with different random subsets
to obtain several ARI values.
2) All obtained ARI values are averaged to obtain the balanced
ARI, that does not depend on the cluster sizes.
RESULTS
The three presented incremental algorithms are evaluated
with the simulated PDW data described in the previous section.
We perform deinterleaving on each of the 4000 scenes
with 100 ms duration for both nonincremental and incremental
processing. Nonincremental algorithms perform deinterleaving
at the end of each scene and therefore can access all
PDWs at once. Incremental algorithms must process each
pulse ofthe scene in sequential order andmust provide immediate
deinterleaving results, according to Figure 1.
Two sets of input features for clustering are analyzed
as follows. The first uses RF and PW, the second AOA
32
and PW. The deinterleaving results are compared to
ground truth data using the balanced ARI. The presented
ARI values are averages over all 4000 simulated scenes.
INCREMENTAL VERSUS NONINCREMENTAL
DEINTERLEAVING
Figure 5 shows the comparison for different incremental
and nonincremental clustering algorithms. We consider
three nonincremental clustering algorithms suitable for
deinterleaving. DBSCAN, HDBSCAN [3], and OPTICS
[2]. Among these nonincremental approaches, DBSCAN
performs best. Interestingly also all three proposed incremental
algorithms achieve a similar ARI as the best nonincremental
algorithm. This first result shows that
incremental deinterleaving does not necessarily imply a
significant loss on deinterleaving accuracy.
INCREMENTAL DEINTERLEAVING WITH RF AND PW
Figure 6 presents the comparison of the incremental algorithms.
The PDW features for clustering are RF and PW.
Four cases are investigated, that have different amounts of
FA pulses. The amount of FA pulses is measured by the
FAR, that is, the number of FA pulses per second. In
IEEE A&E SYSTEMS MAGAZINE
AUGUST 2023
IEEE - Aerospace and Electronic Systems - August 2023
Table of Contents for the Digital Edition of IEEE - Aerospace and Electronic Systems - August 2023
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